u/wineandcodein r/kubernetes • Recommends
#kubecon#edgecomputing#highavailability
Three’s a Crowd: How to Achieve 2-Node HA at the Edge and Make Your CFO Smile
141K subscribers • 77 videos on Hallway • Conference channel
- Recommended by 3 people: 3 in engineering communities.
- Presented by Tyler Gillson & Pedro Oliveira, Spectro Cloud
Intermediate. Assumes working knowledge.
1.2K views2 years ago3 recommendations
Cloud and DevOpsDistributed systemsKubernetesScaling and large-scale architectureFault tolerance and failure
Tyler Gillson and Pedro Oliveira present an architecture for achieving high availability with only two nodes in edge Kubernetes deployments.
Don't miss out! Join us at our next Flagship Conference: KubeCon + CloudNativeCon North America in Salt Lake City from November 12 - 15, 2024. Connect with our current graduated, incubating, and sandbox projects as the community gathers to further the education and advancement of cloud native computing. Learn more at kubecon.io Three’s a Crowd: How to Achieve 2-Node HA at the Edge and Make Your CFO Smile - Tyler Gillson & Pedro Oliveira, Spectro Cloud When you’re scaling production K8s workloads to hundreds or thousands of edge sites, you know you need HA — but with conventional 3-node architectures, the hardware costs can be terrifying. This talk presents a new architecture for 2-node HA that gives you the resilience you need, and 33% cost savings… for a happier meeting with your CFO! It covers: - The challenge: real end user examples from hospitals, coffee shops and factory floors where 3-node HA proved problematic - The problem space: existing alternatives such as external data stores and ‘witnesses’ — and why they fall short - The blueprint: a new OSS-based 2-node HA design built on K3s, Kine, SQLite and Marmot, and the results it’s delivered so far - Your path forward: learnings from building this architecture so you can go forward with confidence!Why it's here
3 people recommend thisWhat people say. Recommended as a viable solution for reducing hardware costs in high-availability edge Kubernetes deployments.
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